Between local innovation and global impact: cities, networks, and the governance of climate change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Global climate governance conducted in settings such as the United Nations Framework Convention on Climate Change (UNFCCC), Major Economies Forum, and Group of Twenty (G20) has proven incapable, to date, of generating an effective response. Greenhouse gas emissions have steadily increased since the issue was added to the global agenda in the early 1990s and prospects appear slim for a single, all-encompassing international legal agreement. Outside the formal regime, however, there are signs of dynamism as non-nation state actors engage in a variety of climate governance experiments. Cities, and city-networks such as the C40 Climate Leadership Group, represent important sources of innovation in the broader system of global climate governance: they challenge prevailing norms regarding who should govern climate change, and how coordinated governance responses can be generated. This paper presents a brief history of the C40, and assesses, drawing on ideas from network theory, some of the opportunities and limitations of networked climate governance. Recognizing that cities, and city-networks, exist within a broader multi-level governance context, the paper concludes with some thoughts related to updating Canadian federal climate policy in order to leverage and enable innovative city-network governance initiatives, address gaps in current federal climate policy, and link climate change to other, pressing issues, on the urban agenda.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it